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Uncertainty quantification patterns for multiscale models

Dongwei Ye, Lourens Veen, Anna Nikishova, Jalal Lakhlili, Wouter Edeling, O. O. Luk, Valeria V. Krzhizhanovskaya, Alfons G. Hoekstra

2021Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences20 citationsDOIOpen Access PDF

Abstract

Uncertainty quantification (UQ) is a key component when using computational models that involve uncertainties, e.g. in decision-making scenarios. In this work, we present uncertainty quantification patterns (UQPs) that are designed to support the analysis of uncertainty in coupled multi-scale and multi-domain applications. UQPs provide the basic building blocks to create tailored UQ for multiscale models. The UQPs are implemented as generic templates, which can then be customized and aggregated to create a dedicated UQ procedure for multiscale applications. We present the implementation of the UQPs with multiscale coupling toolkit Multiscale Coupling Library and Environment 3. Potential speed-up for UQPs has been derived as well. As a proof of concept, two examples of multiscale applications using UQPs are presented. This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico ’.

Topics & Concepts

Uncertainty quantificationComputer scienceMultiscale modelingReliability (semiconductor)Domain (mathematical analysis)Key (lock)Scale (ratio)Computational modelMachine learningArtificial intelligenceMathematicsBioinformaticsQuantum mechanicsComputer securityPower (physics)BiologyMathematical analysisPhysicsGene Regulatory Network AnalysisScientific Computing and Data ManagementSimulation Techniques and Applications